Triple
T5737716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Master |
E126538
|
entity |
| Predicate | associatedWithJerseyNumberOfPerson |
P2651
|
FINISHED |
| Object | 10 (India) |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 10 (India) | Statement: [Little Master, associatedWithJerseyNumberOfPerson, 10 (India)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithJerseyNumberOfPerson Context triple: [Little Master, associatedWithJerseyNumberOfPerson, 10 (India)]
-
A.
jerseyNumber
chosen
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
B.
wearsJerseyFor
Indicates that one entity wears a jersey representing, belonging to, or in support of another entity (such as a team, organization, or individual).
-
C.
jerseyNumberCoached
Indicates that a coach was responsible for coaching a player (or players) who wore a specific jersey number.
-
D.
jerseyNumberManaged
Indicates that an entity is responsible for assigning, organizing, or overseeing jersey numbers for players or team members.
-
E.
reasonForJerseyNumber
Indicates the explanation or motivation behind an entity’s choice of a particular jersey number.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c0083082288190b7478cead6b5430a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0255c8c308190821f968ec41c5078 |
completed | March 22, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69c021c8195481909419808b002628aa |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:47 p.m.